A Hybrid fault diagnosis approach for PV generators based on I-V and P-V characteristics analysis

In this paper, we present a hybrid fault diagnosis approach dedicated for PV generators via current-voltage and power-voltage curves analysis. It is mainly based on two signature generators: a fuzzy logic classifier and a based threshold conventional one. The two classifiers act on the available data by considering three thresholds which are made according to the generator PV typical parameters and with a total conformity with the standards. The proposed fault diagnosis approach requires only the available measured variables and is able to identify the most frequently met faults related to shading, temperature, leakage current and increased series resistance losses. The addressed PV generators are based on one diode model. The overall results have proved the proposed methodology capability in PV faults detection and identification.